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Data-driven load profiles and the dynamics of residential electricity consumption
The dynamics of power consumption constitutes an essential building block for planning and operating sustainable energy systems. Whereas variations in the dynamics of renewable energy generation are reasonably well studied, a deeper understanding of the variations in consumption dynamics is still mi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357012/ https://www.ncbi.nlm.nih.gov/pubmed/35933555 http://dx.doi.org/10.1038/s41467-022-31942-9 |
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author | Anvari, Mehrnaz Proedrou, Elisavet Schäfer, Benjamin Beck, Christian Kantz, Holger Timme, Marc |
author_facet | Anvari, Mehrnaz Proedrou, Elisavet Schäfer, Benjamin Beck, Christian Kantz, Holger Timme, Marc |
author_sort | Anvari, Mehrnaz |
collection | PubMed |
description | The dynamics of power consumption constitutes an essential building block for planning and operating sustainable energy systems. Whereas variations in the dynamics of renewable energy generation are reasonably well studied, a deeper understanding of the variations in consumption dynamics is still missing. Here, we analyse highly resolved residential electricity consumption data of Austrian, German and UK households and propose a generally applicable data-driven load model. Specifically, we disentangle the average demand profiles from the demand fluctuations based purely on time series data. We introduce a stochastic model to quantitatively capture the highly intermittent demand fluctuations. Thereby, we offer a better understanding of demand dynamics, in particular its fluctuations, and provide general tools for disentangling mean demand and fluctuations for any given system, going beyond the standard load profile (SLP). Our insights on the demand dynamics may support planning and operating future-compliant (micro) grids in maintaining supply-demand balance. |
format | Online Article Text |
id | pubmed-9357012 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93570122022-08-08 Data-driven load profiles and the dynamics of residential electricity consumption Anvari, Mehrnaz Proedrou, Elisavet Schäfer, Benjamin Beck, Christian Kantz, Holger Timme, Marc Nat Commun Article The dynamics of power consumption constitutes an essential building block for planning and operating sustainable energy systems. Whereas variations in the dynamics of renewable energy generation are reasonably well studied, a deeper understanding of the variations in consumption dynamics is still missing. Here, we analyse highly resolved residential electricity consumption data of Austrian, German and UK households and propose a generally applicable data-driven load model. Specifically, we disentangle the average demand profiles from the demand fluctuations based purely on time series data. We introduce a stochastic model to quantitatively capture the highly intermittent demand fluctuations. Thereby, we offer a better understanding of demand dynamics, in particular its fluctuations, and provide general tools for disentangling mean demand and fluctuations for any given system, going beyond the standard load profile (SLP). Our insights on the demand dynamics may support planning and operating future-compliant (micro) grids in maintaining supply-demand balance. Nature Publishing Group UK 2022-08-06 /pmc/articles/PMC9357012/ /pubmed/35933555 http://dx.doi.org/10.1038/s41467-022-31942-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Anvari, Mehrnaz Proedrou, Elisavet Schäfer, Benjamin Beck, Christian Kantz, Holger Timme, Marc Data-driven load profiles and the dynamics of residential electricity consumption |
title | Data-driven load profiles and the dynamics of residential electricity consumption |
title_full | Data-driven load profiles and the dynamics of residential electricity consumption |
title_fullStr | Data-driven load profiles and the dynamics of residential electricity consumption |
title_full_unstemmed | Data-driven load profiles and the dynamics of residential electricity consumption |
title_short | Data-driven load profiles and the dynamics of residential electricity consumption |
title_sort | data-driven load profiles and the dynamics of residential electricity consumption |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357012/ https://www.ncbi.nlm.nih.gov/pubmed/35933555 http://dx.doi.org/10.1038/s41467-022-31942-9 |
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